Artificial Immune System Algorithm and Simulated Annealing Algorithm for Scheduling Batches of Parts based on Job Availability Model in a Multi-cell Flexible Manufacturing System

Abstract

The flow shop manufacturing cell scheduling problem with sequence dependent setup time is a topic of great concern for many industrial applications. This paper addresses batch scheduling problem in the Multi cell Flexible Manufacturing System (MCFMS) havingsequence dependent batch set up time with flow shop characteristics. The objective of this research problem is the minimization of makespan. A mathematical model for the research problem is developed in this paper. As the research problem is known to be NP-hard, Artificial Immune Systems (AIS) algorithm and Simulated annealing algorithm (SA) algorithm are developed to solve the problem. Eighty test problems are solved in order to test the proposed algorithms. The quality of solution in terms of makespan obtained by AIS algorithm is found superior to that of the SA algorithm. But in computational point of view, SA algorithm takes shorter time than AIS algorithm to find the near optimal batch sequence. Since the operation parameters of meta-heuristic algorithms normally affect the quality of the solution, Sensitive Analysis is carried out for the test problems by varying the percentage of receptor editing in AIS algorithm.